NVIDIA GPUDirect

Whether you are exploring mountains of geological data, researching solutions to complex scientific problems, or racing to model fast-moving financial markets, you need a computing platform that delivers the highest throughput and lowest latency possible. GPU-accelerated clusters and workstations are widely recognized for providing the tremendous horsepower required by compute-intensive workloads. Compute-intensive applications can provide even faster results with NVIDIA GPUDirect™.

First introduced in June 2010, GPUDirect version 1 supported accelerated communication with network and storage devices. Itwas supported by InfiniBand solutions available from Mellanox and others. In 2011, GPUDirect version 2 added support for peer-to-peer communication between GPUs on the same shared memory server. GPU Direct RDMA, announced in 2013, enables RDMA transfers across an Infiniband network between GPUs in different cluster nodes, bypassing CPU host memory altogether.

GPUDirect peer-to-peer transfers and memory access are supported natively by the CUDA Driver. All you need is CUDA Toolkit v4.0 and R270 drivers (or later) and a system with two or more Fermi- or Kepler-architecture GPUs on the same PCIe bus. For more information on using GPUDirect communication in your applications, please see:

GPUDirect support for RDMA is available now in the latest CUDA Toolkit.

Frequently Asked Questions

Q: My company makes network adaptors / storage devices. How do we enable our products for GPUDirect?
A: Please contact us for more information at gpudirect@nvidia.com

Q: Where can I get more information about GPUDirect support for RDMA?
A: API documentation for Linux driver developers interested in integrating RDMA support is available in the CUDA Toolkit and online.